ecs.c8i.large is a ecs.c8i family (2 vCPUs, 4 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 2 vCPUs, 4 GiB of memory and 0 GB of storage. The pricing starts at 0.0631 USD per hour.
A dedicated dual-core compute instance featuring Intel Xeon processing and a balanced two-gigabytes-per-core memory configuration for predictable workloads.
Compute Optimized
Alibaba Cloud ecs.c8i.large is a compute-optimized virtual server featuring 2 dedicated vCPUs and 2 physical cores powered by an Intel Xeon 8475B processor running at 2.7 GHz. Built on the x86_64 architecture and managed via a KVM hypervisor, this instance provides 4.0 GB of system memory, establishing a 2.0 GB per core ratio. It does not include local storage or integrated GPUs, relying on network-attached storage and offering a baseline network bandwidth of 2 Gbps. With dedicated CPU allocation and a single thread per core design, it delivers predictable processing performance. This configuration is well-suited for entry-level compute-intensive workloads, lightweight web serving, microservices, and small-scale application deployments that require dedicated CPU resources without the memory overhead of general-purpose instances.
Economics
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Workload Profiles
Precomputed compound score for Cache Intensive workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 50% Redis RPS (pipeline=1, SET), 20% Redis RPS (pipeline=16, SET), 10% PassMark Memory Mark (composite), 10% Memory bandwidth (read, 16 MB ~ L3), 10% PassMark single-thread CPU. Rationale for component selection: In-memory key-value store workload, mixing direct Redis performance metrics with memory speed and latency benchmarks, and single-core CPU performance profiles.
Precomputed compound score for CI/CD Build workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 50% Geekbench Clang compilation (multi-core), 10% Geekbench Clang compilation (single-core), 20% stress-ng div16 best-N cores, 5% PassMark integer math, 5% PassMark compression, 5% Brotli compression (multi-core, level 0), 5% PassMark string sorting. Rationale for component selection: Build performance is mainly driven by multi-core compilation throughput, but also bundles single-core compilation speed and general CPU performance, multi-core compression and text/scripting processing.
Precomputed compound score for Compute Heavy Applications workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 15% stress-ng div16 best-N cores, 10% stress-ng div16 single core, 20% PassMark CPU Mark (composite), 10% Memory bandwidth (read, 64 MB), 15% PassMark floating point, 15% PassMark AVX/SSE/FMA (SIMD), 10% PassMark integer math, 5% PassMark physics simulation. Rationale for component selection: Number-crunching workload augmenting raw CPU performance stressing, general CPU performance benchmarks, memory bandwidth, and pure math computation speed like floating point, integer, SIMD (AVX/SSE/FMA) operations.
Precomputed compound score for Data Analysis workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 70% PassMark CPU Mark (composite), 10% Gzip compression (single-core, level 5), 10% Memory bandwidth (read, 64 MB), 10% PassMark Memory Mark (composite). Rationale for component selection: Data analysis and ETL workloads are memory-bandwidth-bound and CPU-throughput-driven. The profile combines general CPU performance and memory bandwidth/latency as the primary drivers, supplemented by single-core compression speed as a proxy for serialisation-heavy ETL tasks.
Precomputed compound score for LLM Inference workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 15% LLM text generation (SmolLM-135M, 128 tok), 15% LLM prompt processing (SmolLM-135M, 512 tok), 15% LLM text generation (Llama 7B, 128 tok), 15% LLM prompt processing (Llama 7B, 512 tok), 15% LLM text generation (Llama-3.3 70B, 128 tok), 15% LLM prompt processing (Llama-3.3 70B, 512 tok), 5% Memory bandwidth (read, 256 MB), 2% PassMark AVX/SSE/FMA (SIMD), 2% PassMark floating point. Rationale for component selection: VRAM and memory-bandwidth-bound LLM inference workload, using direct LLM speed benchmarks at three model sizes, and supplementing with raw memory bandwidth and SIMD performance benchmarks.
Precomputed compound score for Web Server workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 30% Static web RPS (1 KiB, 8 conn/vCPU), 20% Static web RPS (64 KiB, 8 conn/vCPU), 20% Static web throughput (256 KiB, 8 conn/vCPU), 20% OpenSSL AES-256-CBC (16 kB blocks), 5% Gzip compression (multi-core, level 5), 5% PassMark string sorting. Rationale for component selection: Primary workloads drivers are single-process static HTTP serving speed and throughput, text processing, TLS termination, and asset compression.
ecs.c8i.large is a ecs.c8i family (2 vCPUs, 4 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 2 vCPUs, 4 GiB of memory and 0 GB of storage. The pricing starts at 0.0631 USD per hour.
The ecs.c8i.large server is equipped with 2 logical CPU cores on 2 Intel Xeon 8475B physical CPU cores running at max. 2.7 Ghz, 4 GiB of memory, 0 GB of storage, and no GPU. Additional block storage can be attached as needed.
The pricing for ecs.c8i.large servers starts at 0.0631 USD per hour, but the actual price depends on the selected region, zone and server allocation method (e.g. on-demand versus spot pricing options): currently, we track the prices in 3 regions and zones every 5 minutes, and the maximum price stands at 0.0631 USD.
The ecs.c8i.large server is offered by Alibaba Cloud, founded in 2009, headquartered in Zhejiang, China. For more information, visit the Alibaba Cloud homepage.
The ecs.c8i.large server is available in 3 availability zones of the following 3 regions: Hangzhou (CN), Shanghai (CN), Shenzhen (CN).
A dedicated dual-core compute instance featuring Intel Xeon processing and a balanced two-gigabytes-per-core memory configuration for predictable workloads.
